Are there communities dealing with costs-vs-accuracy tradeoffs in Machine Learning?
Welcome to AI.SE ks.and1.

What you're describing could be related to several areas, but since you are looking only for some keywords, I'll suggest some:


You might be interested in anytime learning, which might better be called 'learning that can stop at any time'. A good example of this approach in machine learning is anytime learning for decision trees, as summarized in Esmeir &amp; Markovitch's 2007 JMLR paper
Apart from this, it sounds like you are just describing the regular process of retraining a model when you get more data. For most algorithms, this just amounts to changing the input to your program so that it points at a larger file, containing more records than last time, and maybe buying a faster GPU or CPU to train the model with if it's taking too long with the extra data.


Hopefully, this can help you get started. If you have some more details about your problem, I might be able to suggest some more specific resources.